docstr: This function should be implemented in a way that self._original_predictions should
  be converted to a list of prediction.ObjectPrediction and set to
  self._object_prediction_list. self.mask_threshold can also be utilized.
  Args:
      shift_amount_list: list of list
          To shift the box and mask predictions from sliced image to full sized image, should
          be in the form of List[[shift_x, shift_y],[shift_x, shift_y],...]
      full_shape_list: list of list
          Size of the full image after shifting, should be in the form of
          List[[height, width],[height, width],...]
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code: def _create_object_prediction_list_from_original_predictions(
      self,
      shift_amount_list: Optional[List[List[int]]] = [[0, 0]],
      full_shape_list: Optional[List[List[int]]] = None,
  ):
      """
      This function should be implemented in a way that self._original_predictions should
      be converted to a list of prediction.ObjectPrediction and set to
      self._object_prediction_list. self.mask_threshold can also be utilized.
      Args:
          shift_amount_list: list of list
              To shift the box and mask predictions from sliced image to full sized image, should
              be in the form of List[[shift_x, shift_y],[shift_x, shift_y],...]
          full_shape_list: list of list
              Size of the full image after shifting, should be in the form of
              List[[height, width],[height, width],...]
      """
      raise NotImplementedError()
  
file_path: sahi/sahi/models/base.py
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import numpy
  from sahi.utils.import_utils import is_available
  from sahi.utils.torch import select_device
label_desc: Use image node_id 8 for calling the DetectionModel obj's underlying member method code with example usage: obj._create_object_prediction_list_from_original_predictions(shift_amount_list, full_shape_list) without return types